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During the off-line learning stage, the robot performs paths based on motion model about omnidirectional motion structure and records a set of ordered key images from omnidirectional camera.
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In 2011, Destrempes et al. [ 23] proposed a method for the segmentation of plaques in the sequence of ultrasound B-mode images of carotid arteries based on motion estimation and a Bayesian model.
There are several approaches for how to deal with the problem of scene segmentation based on motion, such as the global parametric motion models [1] [3].
Recently, Chen and Huang proposed two crowd behaviour detection models based on motion [111] and visual with graph and matching [112].
The "model-based" approach, sometimes also referred to as the "machine learning" approach, consists in training models based on motion capture data.
The displacements of the photo targets were given as inputs to the FE model and based on motion of the head center of gravity, the time histories and peak values of the resultant linear and rotational velocities and accelerations of the head were determined.
Features based on motion and periodicity characteristics.
These filters iterate between a prediction step based on the motion model and a correction step based on the measurement model and the current measurement.
Motion compensated prediction (MCP) implemented in most video coding schemes is based on translational motion model.
To further enhance human robot co-navigation, Chung and Huang (2011) investigated the development of a predictive path-planning framework based on pedestrian motion models trained via statistical learning methods.
In [10], IIR filtering was proposed for online motion smoothing based on 2D translational motion model.
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